NPTEL Deep Learning IIT Ropar Assignment 2 Answers 2022
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NPTEL Deep Learning IIT Ropar Assignment
This course can have Associate in Nursing unproctored programming communication conjointly excluding the Proctored communication, please check announcement section for date and time. The programming communication can have a weightage of twenty fifth towards the ultimate score.
- Assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
- ( All assignments in a particular week will be counted towards final scoring – quizzes and programming assignments).
- Unproctored programming exam score = 25% of the average scores obtained as part of Unproctored programming exam – out of 100
- Proctored Exam score =50% of the proctored certification exam score out of 100
UNPROCTORED PROGRAMMING EXAM SCORE >=10/25 AND PROCTORED EXAM SCORE >= 20/50.
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Q1. How many Boolean functions can be designed with 3 inputs?
Ans:- C
Q2. Pick out the function(s) that are not linearly separable?
Ans:- A, D
Q3. Out of the functions that can be designed from n inputs, how many of them are linearly separable?
Ans:-D
Q4. Which of the following statements are TRUE?
Statement I. The given network of perceptrons can be used to implement any complex boolean input functions.
Statement II. Each Wi can be adjusted to get desired output for that input.
Ans:-C
Q5. Consider you are given a Boolean function with 5 inputs. It is represented by a network of perceptrons containing one hidden layer and one output layer with one perceptron. How many perceptrons are there in the hidden layer?
Ans:-A
Q6. Assume you have a perceptron to solve a problem of deciding if a student is eligible for scholarship or not. We have only one input in this case. Bias being 50%. What will be the decision of the model when the student scored 0.49 and 0.51?
Ans:-C
Q7. I. Logistic function is smooth and continuous. II. Logistic function is differentiable.
Ans:-C
Q8. Select all that applies to a learning algorithm.
Ans:-A,C,D
Q9. Sum of squared error is better than sum of errors. Why is this true?
Ans:-B
Q10. Consider a machine learning model, with only one input x and output y. Given training instances, (x,y) = (0.4, 0.3), (1.8, 0.6), w = 1.2, b = -1.4 and the function is logistic sigmoid function. Compute the loss function, L(w,b)=12∑Ni=1(yi−f(xi))2
Ans:-0.0059
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